Wei Chang — accepted AI-conference papers

2021

Adaptive Feature Weight Learning For Robust Clustering Problem with Sparse Constraint

Feiping Nie, Wei Chang, Xuelong Li, Jin Xu, Gongfu Li

ICASSP 2021accepted

Clustering task has been greatly developed in recent years like partition-based and graph-based methods. However, in terms of improving robustness, most existing algorithms only focus on noise and outliers between data, while ignoring the noise in feature space. To deal with this situation, we propo…

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2019

Robust Subspace Clustering by Learning an Optimal Structured Bipartite Graph via Low-rank Representation

Wei Chang, Feiping Nie, Rong Wang, Xuelong Li

ICASSP 2019accepted

This paper addresses the subspace clustering problem based on low-rank representation. Combining with the idea of co-clustering, we proposed to learn an optimal structural bipartite graph. It's different with other classical subspace clustering methods which need spectral clustering as post-processi…

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